Wide Angle Ultrasonic Transmission Tomography by Sparse Preimaged OMP Algorithm
Wide Angle Ultrasonic Transmission Tomography by Sparse Preimaged OMP Algorithm
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DOI：
10.1109/tim.2020.2967116
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发表时间：
2020-09
影响因子：
5.6
通讯作者：
Wei Zhang;C. Tan;F. Dong
中科院分区：
文献类型：
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作者：
Wei Zhang;C. Tan;F. Dong
超声透射层析成像(UTT)图像重建是一个复杂的问题。由于超声换能器的扩散角有限，从相反的换能器获得的有用数据很少，因此图像重建问题是不适定的。传统的逻辑反投影(LBP)算法不能充分处理测量数据的稀疏性。为了采集更多的信息，本文设计了大扩散角的传感器。提出了一种用于UTT图像稀疏重建的稀疏预成像正交匹配追踪(SP-OMP)算法。在UTT系统上与LBP、代数重构技术(ART)、同时迭代重构(SIRT)、Tikhonov和L1正则化等经典算法进行了对比实验。测量了均方误差(MSE)、位置误差(PE)、尺寸误差(SE)、相对误差(RE)和相关系数(CC)等质量参数，表明SP-OMP算法可以提供比传统图像重建算法更高质量的图像。
Image reconstruction for ultrasonic transmission tomography (UTT) is a complex problem. Due to the limited diffusion angle of ultrasonic transducers, few useful data are received from the opposite transducers so the image reconstruction problem is ill-posed. The traditional logic backprojection (LBP) algorithm cannot sufficiently deal with the sparse characteristic of measurement data. In this article, transducers with a large diffusion angle are designed to collect more information. A sparse preimaged orthogonal matching pursuit (SP-OMP) algorithm is presented for UTT image sparse reconstruction. The performance of the proposed algorithm is experimentally evaluated by a UTT system versus classical algorithms such as LBP, algebra reconstruction technique (ART), simultaneous iteration reconstruction (Sirt), Tikhonov, and L1-regularization. The quality parameters such as mean square error (MSE), position error (PE), size error (SE), relative error (RE), and correlation coefficient (CC) are surveyed which indicated that the SP-OMP algorithm could provide higher quality images than those provided by the conventional image reconstruction algorithms.